{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T14:43:01Z","timestamp":1786632181671,"version":"build-2736575974"},"reference-count":45,"publisher":"American Chemical Society (ACS)","issue":"4","license":[{"start":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T00:00:00Z","timestamp":1514505600000},"content-version":"vor","delay-in-days":448,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Providing infrastructure and land uses to encourage active travel (i.e., bicycling and walking) are promising strategies for designing health-promoting cities. Population-level exposure to air pollution during active travel is understudied.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives:<\/jats:title>\n                    <jats:p>Our goals were a) to investigate population-level patterns in exposure during active travel, based on spatial estimates of bicycle traffic, pedestrian traffic, and particulate concentrations; and b) to assess how those exposure patterns are associated with the built environment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We employed facility\u2013demand models (active travel) and land use regression models (particulate concentrations) to estimate block-level (n = 13,604) exposure during rush-hour (1600\u20131800 hours) in Minneapolis, Minnesota. We used the model-derived estimates to identify land use patterns and characteristics of the street network that are health promoting. We also assessed how exposure is correlated with indicators of health disparities (e.g., household income, proportion of nonwhite residents). Our work uses population-level rates of active travel (i.e., traffic flows) rather than the probability of walking or biking (i.e., \u201cwalkability\u201d or \u201cbikeability\u201d) to assess exposure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Active travel often occurs on high-traffic streets or near activity centers where particulate concentrations are highest (i.e., 20\u201342% of active travel occurs on blocks with high population-level exposure). Only 2\u20133% of blocks (3\u20138% of total active travel) are \u201csweet spots\u201d (i.e., high active travel, low particulate concentrations); sweet spots are located a) near but slightly removed from the city-center or b) on off-street trails. We identified 1,721 blocks (~ 20% of local roads) where shifting active travel from high-traffic roads to adjacent low-traffic roads would reduce exposure by ~ 15%. Active travel is correlated with population density, land use mix, open space, and retail area; particulate concentrations were mostly unchanged with land use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Public health officials and urban planners may use our findings to promote healthy transportation choices. When designing health-promoting cities, benefits (physical activity) as well as hazards (air pollution) should be evaluated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Citation:<\/jats:title>\n                    <jats:p>Hankey S, Lindsey G, Marshall JD. 2017. Population-level exposure to particulate air pollution during active travel: planning for low-exposure, health-promoting cities. Environ Health Perspect 125:\u2013534;\u2002http:\/\/dx.doi.org\/10.1289\/EHP442<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1289\/ehp442","type":"journal-article","created":{"date-parts":[[2016,10,6]],"date-time":"2016-10-06T14:35:59Z","timestamp":1475764559000},"page":"527-534","source":"Crossref","is-referenced-by-count":78,"title":["Population-Level Exposure to Particulate Air Pollution during Active Travel: Planning for Low-Exposure, Health-Promoting Cities"],"prefix":"10.1021","volume":"125","author":[{"given":"Steve","family":"Hankey","sequence":"first","affiliation":[{"name":"School of Public and International Affairs, Virginia Tech, Blacksburg, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Greg","family":"Lindsey","sequence":"additional","affiliation":[{"name":"Humphrey School of Public Affairs, University of Minnesota, Minneapolis, Minnesota, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian D.","family":"Marshall","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2016,10,7]]},"reference":[{"key":"2026080314115728500_micit1","article-title":"Making Healthy Places: Designing and Building for Health, Well-Being, and Sustainability.","author":"Abrams RF, Malizia E, Wendel A, Sallis J, Millstein RA, Carlson JA, et al","year":"2012"},{"issue":"11","key":"2026080314115728500_micit2","doi-asserted-by":"crossref","first-page":"4914","DOI":"10.1021\/es103866b","article-title":"Effects of income and urban form on urban NO2: global evidence from satellites.","volume":"45","author":"Bechle","year":"2011","journal-title":"Environ Sci Technol"},{"issue":"9919","key":"2026080314115728500_micit3","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1016\/S0140-6736(13)62158-3","article-title":"Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicenter ESCAPE project.","volume":"383","author":"Beelen","year":"2014","journal-title":"Lancet"},{"issue":"2","key":"2026080314115728500_micit4","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1006\/jeem.1996.0967","article-title":"The distribution of pollution: community characteristics and exposure to air toxics.","volume":"32","author":"Brooks","year":"1997","journal-title":"J Environ Econ Manage"},{"issue":"4","key":"2026080314115728500_micit5","doi-asserted-by":"publisher","first-page":"e94431","DOI":"10.1371\/journal.pone.0094431","article-title":"National patterns in environmental injustice and inequality: outdoor NO2 air pollution in the United States.","volume":"9","author":"Clark","year":"2014","journal-title":"PLoS One"},{"key":"2026080314115728500_micit6","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.trd.2015.07.004","article-title":"Objective correlates and determinants of bicycle commuting propensity in an urban environment.","volume":"40","author":"Cole-Hunter","year":"2015","journal-title":"Transp Res D Transp Environ"},{"key":"2026080314115728500_micit7","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.atmosenv.2012.06.041","article-title":"Inhaled particle counts on bicycle commute routes of low and high proximity to motorised traffic.","volume":"61","author":"Cole-Hunter","year":"2012","journal-title":"Atmos Environ"},{"key":"2026080314115728500_micit8","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1038\/jes.2015.66","article-title":"Impact of traffic-related air pollution on acute changes in cardiac autonomic modulation during rest and physical activity: a cross-over study.","volume":"26","author":"Cole-Hunter","year":"2016","journal-title":"J Expo Sci Environ Epidemiol"},{"issue":"5","key":"2026080314115728500_micit9","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1038\/jes.2014.89","article-title":"Within- and between-city contrasts in nitrogen dioxide and mortality in 10 Canadian cities; 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